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Data Management at CSHL: Home

Introduction to Data Management

Data management is "the development, execution and supervision of plans, policies, programs and practices that control, protect, deliver and enhance the value of data and information assets".
In a scientific, academic setting this means developing plans and policies for how data generated in the laboratory, as a result of experimentation, is stored and saved so it can be used and more easily understood by scientists other than those that originally generated it.

What is Data?

There are a number of definitions for what data is and here are a few of them
Here are some definitions:

From the Merriam-Webster Dictionary

  1. 1 :  factual information (such as measurements or statistics) used as a basis for reasoning, discussion, or calculation the data is plentiful and easily available — H. A. Gleason, Jr. comprehensive data on economic growth have been published — N. H. Jacoby

  2. 2 :  information output by a sensing device or organ that includes both useful and irrelevant or redundant information and must be processed to be meaningful

  3. 3 :  information in numerical form that can be digitally transmitted or processed

From the Digital Curation Center

Data, any information in binary digital form, is at the centre of the Curation Lifecycle.

From the Office of Management and Budget
“Research data means the recorded
factual material commonly accepted in the scientific community as necessary to validate research findings” 

Across all scientific fields data is generated and the types of data include

  • observational data
  • experimental data
  • computer simulation
  • quantitative data
  • qualitative data

Data can also be categorised as "Raw" or "Processed"

Examples of raw data:

  • Images
  • Gels
  • Behavioural Records
  • Electrophysiology records
  • Unaligned Sequence data

Examples of processed data:

  • Spreadsheets
  • Graphs
  • Tables
  • Aligned Sequence data

Why is Data Management important

  • Makes it easier to generate the information required for publication
  • Increases the discoverability and shareability of the data in your publication .
  • Decreases the likelihood of catastrophic data loss
  • Meets important funder mandates
  • Saves everyone time and money

Science Informationist

Matthew Covey's picture
Matthew Covey
Contact:
CSHL - Library & Archives
One Bungtown Rd
Cold Spring Harbor, NY 11724
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